If you’re interested in learning more about RAships or gaining some of the skills that might be helpful as an RA (and in research more generally!), here’s a list of some resources to explore.
- Causal Inference: The Mix Tape (Scott Cunningham): covers the essential causal inference strategies, including help with coding them up in Stata. Also has a companion Spotify playlist!
- Running Randomized Evaluations: A Practical Guide (Glennester), and corresponding website
- David McKenzie’s monster list on how to run studies in the developing world from the World Bank Blogs
General research computing skills
- Software Carpentry: includes lessons on Unix Shell, Git, Python and R.
- Germán Rodríguez’s Stata tutorial
- A Gentle Introduction to Stata, by Alan Acock
- Alexander Lembcke’s introduction to Stata, parts A and B
- Jack Blundell’s online Applied Econometrics in Stata course
- Germán Rodríguez’s introduction to R
Coding and data management principles
- Gentzkow and Shapiro’s Code and Data for the Social Sciences: A Practitioner’s Guide
- Gentzkow and Shapiro’s Internal RA Manual
- Michael Stepner’s coding style guide
- World Bank Development Impact Evaluation (DIME)’s Wiki
- Innovations for Poverty Action (IPA)’s Best Practice Guide
- Jesse Shapiro on…
- Jonathan Schwabish’s An Economist’s Guide to Visualizing Data